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At time of writing, generative AI guidance and “how to” instructional posts are flooding the social media ecosystem. Most are threads showcasing the newest tool and full of promise: improve productivity, save time, increase sales. But something seems off. Their tone and structure all seem eerily similar—a telling sign that they were crafted by AI to capitalize on the surge of interest.

In the din of online content and slick marketing, the worst thing you can do is try and keep up with every post and newsletter advertising a new tool. This would be an impossible task that would bury you in links and tutorials. The resulting content shock risks obscuring the true value of generative AI. To use a tired idiom: We’d fail to “see the forest for the trees” when bogged down with every new product or feature.

I propose here a measured approach and a framework for thinking about this powerful technology and how to best incorporate it into a team or workflow.

Moving forward: A mix of human and machine

Rather than replacing human work outright, the knowledge sector can marry the best of both worlds: AI can replace the rote, unfulfilling tasks that can be easily automated; and humans should guide strategy informed by experience and context, and add creativity to campaigns and projects.

Two areas where generative AI currently underperform are context and nuance. Algorithms have a much harder time emulating these, and they’re important variables that should guide informed decision making. “Guidelines never rules” was the adage we carried as young journalists in j-school. Situations can differ and recognizing this is important as life is not a series of equations to be followed with predictable outcomes.

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Consider a hybrid model where time-consuming, repetitive tasks are given to AI, along with specialized tasks that take too long to complete. Humans can then add value to a team or process by adding insights from experience, apply theory, and put information into context to help develop better strategy and project design. The two—artificial intelligence and human reasoning—work together, not at cross purposes. Importantly, layered overtop of this is recognizing the audience. If a deliverable is meant for a high-value stakeholder and it’s critical to get it right, then more human involvement is necessary.

Another dimension to consider is how we decide on the specific role AI will play on our teams and in our workplaces; more specifically, what are the ethical parameters of usage and what tools do we incorporate and when. As noted earlier, there’s currently no shortage of must have tools and applications and it’s easy to feel overwhelmed. Here, it’s human judgment and intuition that should help us slow down and take a more measured look.

Helpful tips on tools

Don’t try and keep up with the cascade of social media and newsletter updates on generative AI. There are simply too many marketing emails and social media twittorials online clamoring for our attention and trying to capitalize on our fear of missing out. Instead, scan them for usefulness, author credibility (how long have they been writing about this topic?), and bookmark/subscribe to only those you find useful—trust your instincts.

Be skeptical. Question whether the time it takes to learn a new tool will be worth it. Don’t feel guilty ignoring some, and ask yourself:

• How useful is this?
• Will I use it?
• How much time will it save me?
• Am I learning it for its own sake or because I actually need it?
• Does it do something that Google Gemini, ChatGPT, or Claude can’t?

Never pay for a plan without thoroughly trying the service. Many new tools will lure you with free content creation, but force you to pay when you need to export and share what you’ve made.

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With regard to individual and team workflows, consider the following:

• Is there a task I/we do frequently that is low stakes but takes up a lot of time?
• Is there a highly specialized, time-consuming task I/we do less frequently that could be offloaded to generative AI (e.g., web scraping or image enhancement)?
• What is the barrier to entry for this new tool and how easy is it to learn?

READ MORE: Artificial intelligence set to reshape the employment landscape

Formulate guidelines for your team. Read analyses from journalists and thought leaders about the ethical implications of generative AI and its impact on society. The prevailing view is that AI can exponentially widen the gap in power and inequality between those who have and those who don’t. But it also has the potential to invigorate the economy and productivity, and find new cures and treatments for disease. Take a balanced look and examine all sides.

Philosophy and approach

Concerning how much to integrate generative AI into your team’s workflow, take a strategic and focused approach rather than implementing it aggressively and broadly throughout. Target areas that will drive the most value rather than adopting AI for its own sake simply because it has been dominating news headlines and public discourse. Ask yourself: What is taking up a lot of time that can be automated? What specific tasks can I not do now that AI can?

With the increased efficiency and time savings AI will afford, encourage your team to redirect their freed-up capacity to creativity and innovation—thinking outside the box and coming up with newer, bolder approaches and content ideas. Generative AI can free up mental bandwidth to think at a higher level with a wider field of view–the forest, not trees.

Some of my favorite tools

These are some of the tools I’ve personally found most useful:

• Gemini is an excellent all-purpose generative AI tool.
• Copy.ai is a good content generator for marketing copy (content reviews), HR templates (job descriptions), and case studies or reports.
• SciSpace Copilot helps distill complex academic studies.
• ChatPDF summarizes and explores PDF documents.
• Kaiber is a paid video creator that is especially useful for animating abstract concepts and ideas.
• Scribe is good for creating SOP and guidance documentation from screen records.

In addition to specific tools, make use of tool libraries like SuperTools and AI Search to meet specific needs.

Judging by the speed of adoption, with nearly every technology company rolling out generative AI features in their products, it’s clear we’re at a turning point in history. This wave of innovation will change the way we access information, work, and interact with others. With such broad impacts, it’s important to get ahead of these changes so that they can be steered in the right direction and help society rather than solely generate profit. But doing so involves learning and embracing innovation, not hiding from it.